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COSMIC Cancer Gene Census 3D database: understanding the impacts of mutations on cancer targets.
Alsulami, Ali F; Torres, Pedro H M; Moghul, Ismail; Arif, Sheikh Mohammed; Chaplin, Amanda K; Vedithi, Sundeep Chaitanya; Blundell, Tom L.
Afiliação
  • Alsulami AF; Department of Biochemistry at the University of Cambridge, Cambridge CB2 1GA, UK.
  • Torres PHM; Laboratório de Modelagem e Dinâmica Molecular, Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, RJ, Brasil.
  • Moghul I; UCL Cancer Institute, University College London, UK.
  • Arif SM; Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
  • Chaplin AK; Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
  • Vedithi SC; Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
  • Blundell TL; Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK.
Brief Bioinform ; 22(6)2021 11 05.
Article em En | MEDLINE | ID: mdl-34137435
ABSTRACT
Mutations in hallmark genes are believed to be the main drivers of cancer progression. These mutations are reported in the Catalogue of Somatic Mutations in Cancer (COSMIC). Structural appreciation of where these mutations appear, in protein-protein interfaces, active sites or deoxyribonucleic acid (DNA) interfaces, and predicting the impacts of these mutations using a variety of computational tools are crucial for successful drug discovery and development. Currently, there are 723 genes presented in the COSMIC Cancer Gene Census. Due to the complexity of the gene products, structures of only 87 genes have been solved experimentally with structural coverage between 90% and 100%. Here, we present a comprehensive, user-friendly, web interface (https//cancer-3d.com/) of 714 modelled cancer-related genes, including homo-oligomers, hetero-oligomers, transmembrane proteins and complexes with DNA, ribonucleic acid, ligands and co-factors. Using SDM and mCSM software, we have predicted the impacts of reported mutations on protein stability, protein-protein interfaces affinity and protein-nucleic acid complexes affinity. Furthermore, we also predicted intrinsically disordered regions using DISOPRED3.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Oncogenes / Software / Biomarcadores Tumorais / Biologia Computacional / Bases de Dados Genéticas / Mutação / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Oncogenes / Software / Biomarcadores Tumorais / Biologia Computacional / Bases de Dados Genéticas / Mutação / Neoplasias Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article